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1. Introduction
IS NUCLEAR GENERATOR A GOOD SOURCE OF ELECTRICITY POWER? IF NOT,
WHAT ARE SOME GOOD ALTERNATIVES?
In this data set, we will be exploring a good source of power which
we can use for a long time. The power source we will be exploring and
analyzing will be Nuclear Power. Nuclear power is a form of energy
production that harnesses the energy released from nuclear reactions.
Nuclear power plants typically use fission to generate electricity. They
are known for providing large amounts of continuous power and have low
greenhouse gas emissions during operation.
For a step-by-step process on what will be done in this analysis, we
will first explore which country will produce the most nuclear energy
and see how much electricity is produced from them throughout the years
on average. Secondly, we will see from those countries, what other
source of power are they using which can be a good/viable alternative
power source if Nuclear Energy isn’t working. Finally, we will see the
trend of Nuclear energy across 10 years which is a good time frame to
analyze the rise and fall of it and see if it will hold up for use in
the future.
2.1 Data Summary
World Nuclear Generation
Firstly, wee will see the top countries which uses Nuclear Energy and
see their electricity generation and electricity share.
#> Rows: 9603 Columns: 4
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (1): Entity
#> dbl (3): Year, electricity_from_nuclear_twh, share_of_electricity_pct
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Entity Year electricity_from_nuclear_twh share_of_electricity_pct
#> 1 Afghanistan 2000 0 0
#> 2 Afghanistan 2001 0 0
#> 3 Afghanistan 2002 0 0
#> 4 Afghanistan 2003 0 0
#> 5 Afghanistan 2004 0 0
#> 6 Afghanistan 2005 0 0
#> Entity Year electricity_from_nuclear_twh
#> Length:9603 Min. :1965 Min. : 0.00
#> Class :character 1st Qu.:1987 1st Qu.: 0.00
#> Mode :character Median :2003 Median : 0.00
#> Mean :2000 Mean : 88.80
#> 3rd Qu.:2013 3rd Qu.: 3.97
#> Max. :2023 Max. :2762.24
#>
#> share_of_electricity_pct
#> Min. : 0.000
#> 1st Qu.: 0.000
#> Median : 0.000
#> Mean : 5.803
#> 3rd Qu.: 2.461
#> Max. :88.011
#> NA's :2457
#> 'data.frame': 9603 obs. of 4 variables:
#> $ Entity : chr "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
#> $ Year : num 2000 2001 2002 2003 2004 ...
#> $ electricity_from_nuclear_twh: num 0 0 0 0 0 0 0 0 0 0 ...
#> $ share_of_electricity_pct : num 0 0 0 0 0 0 0 0 0 0 ...
3.1 Data Preprocessing Data Set
Missing Data Checking and Filling
#> [1] 2457
#> Entity Year
#> 0 0
#> electricity_from_nuclear_twh share_of_electricity_pct
#> 0 2457
From the data shown above we can conclude that all of the mssing data
from the ‘World Nuclear Generation’ dataset are in the
‘share_of_electricity_pct’ column. From this data, we decided to fill
all this n/a value with 0 since we can’t delete it or it will
significantly alter the dataset and we can’t fill it with mean value or
it will also alter our dataset.
#> [1] 0
#> Entity Year
#> 0 0
#> electricity_from_nuclear_twh share_of_electricity_pct
#> 0 0
Duplicate Variables Checking
#> [1] 0
Here, we can see that there are no duplicate variables which means
that we don’t need to clean our data from any duplicate variables.
4.1 Data Exploration
#> # A tibble: 6 × 3
#> Entity avgElectricityFromNuclear avgElectricityShare
#> <chr> <dbl> <dbl>
#> 1 Afghanistan 0 0
#> 2 Africa 7.55 1.50
#> 3 Africa (EI) 7.55 1.50
#> 4 Africa (Ember) 12.3 1.85
#> 5 Albania 0 0
#> 6 Algeria 0 0
Average Electricity Generation and Share
Electricity Generation
#> # A tibble: 6 × 2
#> Entity avgElectricityFromNuclear
#> <chr> <dbl>
#> 1 G20 (Ember) 2477.
#> 2 OECD (Ember) 2074.
#> 3 World 1745.
#> 4 G7 (Ember) 1632.
#> 5 High-income countries 1449.
#> 6 OECD (EI) 1441.
We want to calculate the top 5 countries with the most average
electricty from nuclear generation and since the top 5 are not
countries, we can drop them and redo the dataframe.
#> # A tibble: 6 × 2
#> Entity avgElectricityFromNuclear
#> <chr> <dbl>
#> 1 Europe (Ember) 1167.
#> 2 North America (Ember) 881.
#> 3 Europe 800.
#> 4 Europe (EI) 687.
#> 5 North America (EI) 611.
#> 6 North America 594.
Here we can see that United States, France, Russia, Japan and Germany
are the countries with the most electricity from nuclear energy on
average. There are more generation from each country but we want to see
the top 5 from the whole country. Thus we pick those 5 as the top.
5.1.1 Statistical Analysis
#> No trace type specified:
#> Based on info supplied, a 'bar' trace seems appropriate.
#> Read more about this trace type -> https://plotly.com/r/reference/#bar
Here we can see that the United States produced or used the most
Nuclear Energy with a whopping 529 MW of energy on average through the
years. It is then followed by France in 2nd, Russia in 3rd, Japan in 4th
and Germany in 5th. We can see these are top countries which produced
the most electricity power through Nuclear energy.
Electricity Share
#> # A tibble: 6 × 3
#> Entity avgElectricityFromNuclear avgElectricityShare
#> <chr> <dbl> <dbl>
#> 1 Armenia 2.22 33.7
#> 2 Sweden 48.0 28.4
#> 3 Hungary 9.45 27.8
#> 4 Switzerland 18.8 25.7
#> 5 Bulgaria 11.8 24.5
#> 6 Europe (Ember) 1167. 23.6
Here we can see that the top 5 countries with electical shares are
Armenia, Sweden, Hungary, Switzerland, and Bulgaria.
5.1.2 Statistical Analysis
#> No trace type specified:
#> Based on info supplied, a 'bar' trace seems appropriate.
#> Read more about this trace type -> https://plotly.com/r/reference/#bar
Here we can see that Armenia is the leading country which produced
the most electricity share through the years and its followed by Sweden,
then Hungary, then Switzerland, and finally Bulgaria.
2.2 Data Summary
Global Nuclear Power Plant
#> Rows: 34936 Columns: 36
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (18): country, country_long, name, gppd_idnr, primary_fuel, other_fuel1,...
#> dbl (17): capacity_mw, latitude, longitude, commissioning_year, year_of_capa...
#> lgl (1): other_fuel3
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> country country_long
#> 1 AFG Afghanistan
#> 2 AFG Afghanistan
#> 3 AFG Afghanistan
#> 4 AFG Afghanistan
#> 5 AFG Afghanistan
#> 6 AFG Afghanistan
#> name gppd_idnr
#> 1 Kajaki Hydroelectric Power Plant Afghanistan GEODB0040538
#> 2 Kandahar DOG WKS0070144
#> 3 Kandahar JOL WKS0071196
#> 4 Mahipar Hydroelectric Power Plant Afghanistan GEODB0040541
#> 5 Naghlu Dam Hydroelectric Power Plant Afghanistan GEODB0040534
#> 6 Nangarhar (Darunta) Hydroelectric Power Plant Afghanistan GEODB0040536
#> capacity_mw latitude longitude primary_fuel other_fuel1 other_fuel2
#> 1 33.00 32.3220 65.1190 Hydro <NA> <NA>
#> 2 10.00 31.6700 65.7950 Solar <NA> <NA>
#> 3 10.00 31.6230 65.7920 Solar <NA> <NA>
#> 4 66.00 34.5560 69.4787 Hydro <NA> <NA>
#> 5 100.00 34.6410 69.7170 Hydro <NA> <NA>
#> 6 11.55 34.4847 70.3633 Hydro <NA> <NA>
#> other_fuel3 commissioning_year owner source
#> 1 NA NA <NA> GEODB
#> 2 NA NA <NA> Wiki-Solar
#> 3 NA NA <NA> Wiki-Solar
#> 4 NA NA <NA> GEODB
#> 5 NA NA <NA> GEODB
#> 6 NA NA <NA> GEODB
#> url geolocation_source wepp_id
#> 1 http://globalenergyobservatory.org GEODB 1009793
#> 2 https://www.wiki-solar.org Wiki-Solar <NA>
#> 3 https://www.wiki-solar.org Wiki-Solar <NA>
#> 4 http://globalenergyobservatory.org GEODB 1009795
#> 5 http://globalenergyobservatory.org GEODB 1009797
#> 6 http://globalenergyobservatory.org GEODB 1009787
#> year_of_capacity_data generation_gwh_2013 generation_gwh_2014
#> 1 2017 NA NA
#> 2 NA NA NA
#> 3 NA NA NA
#> 4 2017 NA NA
#> 5 2017 NA NA
#> 6 2017 NA NA
#> generation_gwh_2015 generation_gwh_2016 generation_gwh_2017
#> 1 NA NA NA
#> 2 NA NA NA
#> 3 NA NA NA
#> 4 NA NA NA
#> 5 NA NA NA
#> 6 NA NA NA
#> generation_gwh_2018 generation_gwh_2019 generation_data_source
#> 1 NA NA <NA>
#> 2 NA NA <NA>
#> 3 NA NA <NA>
#> 4 NA NA <NA>
#> 5 NA NA <NA>
#> 6 NA NA <NA>
#> estimated_generation_gwh_2013 estimated_generation_gwh_2014
#> 1 123.77 162.90
#> 2 18.43 17.48
#> 3 18.64 17.58
#> 4 225.06 203.55
#> 5 406.16 357.22
#> 6 58.77 54.42
#> estimated_generation_gwh_2015 estimated_generation_gwh_2016
#> 1 97.39 137.76
#> 2 18.25 17.70
#> 3 19.10 17.62
#> 4 146.90 230.18
#> 5 270.99 395.38
#> 6 42.71 59.72
#> estimated_generation_gwh_2017 estimated_generation_note_2013
#> 1 119.50 HYDRO-V1
#> 2 18.29 SOLAR-V1-NO-AGE
#> 3 18.72 SOLAR-V1-NO-AGE
#> 4 174.91 HYDRO-V1
#> 5 350.80 HYDRO-V1
#> 6 46.12 HYDRO-V1
#> estimated_generation_note_2014 estimated_generation_note_2015
#> 1 HYDRO-V1 HYDRO-V1
#> 2 SOLAR-V1-NO-AGE SOLAR-V1-NO-AGE
#> 3 SOLAR-V1-NO-AGE SOLAR-V1-NO-AGE
#> 4 HYDRO-V1 HYDRO-V1
#> 5 HYDRO-V1 HYDRO-V1
#> 6 HYDRO-V1 HYDRO-V1
#> estimated_generation_note_2016 estimated_generation_note_2017
#> 1 HYDRO-V1 HYDRO-V1
#> 2 SOLAR-V1-NO-AGE SOLAR-V1-NO-AGE
#> 3 SOLAR-V1-NO-AGE SOLAR-V1-NO-AGE
#> 4 HYDRO-V1 HYDRO-V1
#> 5 HYDRO-V1 HYDRO-V1
#> 6 HYDRO-V1 HYDRO-V1
After knowing the top 5 Countries for electricity share and
electricity produced from nuclear energy, we can see what other power
plant those countries used and see their electricity generation.
#> country country_long name gppd_idnr
#> Length:34936 Length:34936 Length:34936 Length:34936
#> Class :character Class :character Class :character Class :character
#> Mode :character Mode :character Mode :character Mode :character
#>
#>
#>
#>
#> capacity_mw latitude longitude primary_fuel
#> Min. : 1.00 Min. :-77.85 Min. :-179.978 Length:34936
#> 1st Qu.: 4.90 1st Qu.: 29.26 1st Qu.: -77.642 Class :character
#> Median : 16.75 Median : 39.73 Median : -2.127 Mode :character
#> Mean : 163.35 Mean : 32.82 Mean : -6.973
#> 3rd Qu.: 75.34 3rd Qu.: 46.26 3rd Qu.: 49.503
#> Max. :22500.00 Max. : 71.29 Max. : 179.389
#>
#> other_fuel1 other_fuel2 other_fuel3 commissioning_year
#> Length:34936 Length:34936 Mode:logical Min. :1896
#> Class :character Class :character NA's:34936 1st Qu.:1988
#> Mode :character Mode :character Median :2007
#> Mean :1997
#> 3rd Qu.:2014
#> Max. :2020
#> NA's :17489
#> owner source url geolocation_source
#> Length:34936 Length:34936 Length:34936 Length:34936
#> Class :character Class :character Class :character Class :character
#> Mode :character Mode :character Mode :character Mode :character
#>
#>
#>
#>
#> wepp_id year_of_capacity_data generation_gwh_2013
#> Length:34936 Min. :2000 Min. : -947.60
#> Class :character 1st Qu.:2017 1st Qu.: 1.95
#> Mode :character Median :2019 Median : 23.43
#> Mean :2018 Mean : 592.70
#> 3rd Qu.:2019 3rd Qu.: 199.71
#> Max. :2019 Max. :50834.00
#> NA's :20049 NA's :28519
#> generation_gwh_2014 generation_gwh_2015 generation_gwh_2016
#> Min. : -989.62 Min. : -864.43 Min. : -768.62
#> 1st Qu.: 2.26 1st Qu.: 2.66 1st Qu.: 2.73
#> Median : 23.61 Median : 26.14 Median : 22.46
#> Mean : 656.86 Mean : 762.37 Mean : 693.15
#> 3rd Qu.: 226.32 3rd Qu.: 285.86 3rd Qu.: 249.87
#> Max. :32320.92 Max. :37433.61 Max. :32377.48
#> NA's :27710 NA's :26733 NA's :25792
#> generation_gwh_2017 generation_gwh_2018 generation_gwh_2019
#> Min. : -934.94 Min. : -982.62 Min. : -780.34
#> 1st Qu.: 2.47 1st Qu.: 2.24 1st Qu.: 2.75
#> Median : 17.88 Median : 12.53 Median : 11.53
#> Mean : 661.83 Mean : 517.32 Mean : 423.92
#> 3rd Qu.: 214.51 3rd Qu.: 151.12 3rd Qu.: 122.78
#> Max. :36448.64 Max. :35136.00 Max. :31920.37
#> NA's :25436 NA's :25299 NA's :25277
#> generation_data_source estimated_generation_gwh_2013
#> Length:34936 Min. : 1.12
#> Class :character 1st Qu.: 8.62
#> Mode :character Median : 27.62
#> Mean : 239.11
#> 3rd Qu.: 106.81
#> Max. :48675.06
#> NA's :18816
#> estimated_generation_gwh_2014 estimated_generation_gwh_2015
#> Min. : 0.87 Min. : 0.44
#> 1st Qu.: 8.68 1st Qu.: 8.38
#> Median : 28.25 Median : 26.83
#> Mean : 242.43 Mean : 235.87
#> 3rd Qu.: 106.98 3rd Qu.: 103.12
#> Max. :58470.77 Max. :57113.35
#> NA's :18433 NA's :17886
#> estimated_generation_gwh_2016 estimated_generation_gwh_2017
#> Min. : 0.30 Min. : 0.00
#> 1st Qu.: 8.32 1st Qu.: 8.18
#> Median : 27.56 Median : 37.59
#> Mean : 235.70 Mean : 716.44
#> 3rd Qu.: 107.24 3rd Qu.: 229.56
#> Max. :60859.73 Max. :82810.77
#> NA's :17366 NA's :1798
#> estimated_generation_note_2013 estimated_generation_note_2014
#> Length:34936 Length:34936
#> Class :character Class :character
#> Mode :character Mode :character
#>
#>
#>
#>
#> estimated_generation_note_2015 estimated_generation_note_2016
#> Length:34936 Length:34936
#> Class :character Class :character
#> Mode :character Mode :character
#>
#>
#>
#>
#> estimated_generation_note_2017
#> Length:34936
#> Class :character
#> Mode :character
#>
#>
#>
#>
#> 'data.frame': 34936 obs. of 36 variables:
#> $ country : chr "AFG" "AFG" "AFG" "AFG" ...
#> $ country_long : chr "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
#> $ name : chr "Kajaki Hydroelectric Power Plant Afghanistan" "Kandahar DOG" "Kandahar JOL" "Mahipar Hydroelectric Power Plant Afghanistan" ...
#> $ gppd_idnr : chr "GEODB0040538" "WKS0070144" "WKS0071196" "GEODB0040541" ...
#> $ capacity_mw : num 33 10 10 66 100 ...
#> $ latitude : num 32.3 31.7 31.6 34.6 34.6 ...
#> $ longitude : num 65.1 65.8 65.8 69.5 69.7 ...
#> $ primary_fuel : chr "Hydro" "Solar" "Solar" "Hydro" ...
#> $ other_fuel1 : chr NA NA NA NA ...
#> $ other_fuel2 : chr NA NA NA NA ...
#> $ other_fuel3 : logi NA NA NA NA NA NA ...
#> $ commissioning_year : num NA NA NA NA NA ...
#> $ owner : chr NA NA NA NA ...
#> $ source : chr "GEODB" "Wiki-Solar" "Wiki-Solar" "GEODB" ...
#> $ url : chr "http://globalenergyobservatory.org" "https://www.wiki-solar.org" "https://www.wiki-solar.org" "http://globalenergyobservatory.org" ...
#> $ geolocation_source : chr "GEODB" "Wiki-Solar" "Wiki-Solar" "GEODB" ...
#> $ wepp_id : chr "1009793" NA NA "1009795" ...
#> $ year_of_capacity_data : num 2017 NA NA 2017 2017 ...
#> $ generation_gwh_2013 : num NA NA NA NA NA NA NA NA NA NA ...
#> $ generation_gwh_2014 : num NA NA NA NA NA NA NA NA NA NA ...
#> $ generation_gwh_2015 : num NA NA NA NA NA NA NA NA NA NA ...
#> $ generation_gwh_2016 : num NA NA NA NA NA NA NA NA NA NA ...
#> $ generation_gwh_2017 : num NA NA NA NA NA NA NA NA NA NA ...
#> $ generation_gwh_2018 : num NA NA NA NA NA NA NA NA NA NA ...
#> $ generation_gwh_2019 : num NA NA NA NA NA NA NA NA NA NA ...
#> $ generation_data_source : chr NA NA NA NA ...
#> $ estimated_generation_gwh_2013 : num 123.8 18.4 18.6 225.1 406.2 ...
#> $ estimated_generation_gwh_2014 : num 162.9 17.5 17.6 203.6 357.2 ...
#> $ estimated_generation_gwh_2015 : num 97.4 18.2 19.1 146.9 271 ...
#> $ estimated_generation_gwh_2016 : num 137.8 17.7 17.6 230.2 395.4 ...
#> $ estimated_generation_gwh_2017 : num 119.5 18.3 18.7 174.9 350.8 ...
#> $ estimated_generation_note_2013: chr "HYDRO-V1" "SOLAR-V1-NO-AGE" "SOLAR-V1-NO-AGE" "HYDRO-V1" ...
#> $ estimated_generation_note_2014: chr "HYDRO-V1" "SOLAR-V1-NO-AGE" "SOLAR-V1-NO-AGE" "HYDRO-V1" ...
#> $ estimated_generation_note_2015: chr "HYDRO-V1" "SOLAR-V1-NO-AGE" "SOLAR-V1-NO-AGE" "HYDRO-V1" ...
#> $ estimated_generation_note_2016: chr "HYDRO-V1" "SOLAR-V1-NO-AGE" "SOLAR-V1-NO-AGE" "HYDRO-V1" ...
#> $ estimated_generation_note_2017: chr "HYDRO-V1" "SOLAR-V1-NO-AGE" "SOLAR-V1-NO-AGE" "HYDRO-V1" ...
3.2 Data Preprocessing
Missing Data Variable and Filling
#> [1] 455949
#> country country_long
#> 0 0
#> name gppd_idnr
#> 0 0
#> capacity_mw latitude
#> 0 0
#> longitude primary_fuel
#> 0 0
#> other_fuel1 other_fuel2
#> 32992 34660
#> other_fuel3 commissioning_year
#> 34936 17489
#> owner source
#> 14068 15
#> url geolocation_source
#> 18 419
#> wepp_id year_of_capacity_data
#> 18702 20049
#> generation_gwh_2013 generation_gwh_2014
#> 28519 27710
#> generation_gwh_2015 generation_gwh_2016
#> 26733 25792
#> generation_gwh_2017 generation_gwh_2018
#> 25436 25299
#> generation_gwh_2019 generation_data_source
#> 25277 23536
#> estimated_generation_gwh_2013 estimated_generation_gwh_2014
#> 18816 18433
#> estimated_generation_gwh_2015 estimated_generation_gwh_2016
#> 17886 17366
#> estimated_generation_gwh_2017 estimated_generation_note_2013
#> 1798 0
#> estimated_generation_note_2014 estimated_generation_note_2015
#> 0 0
#> estimated_generation_note_2016 estimated_generation_note_2017
#> 0 0
From the data above, there seems to be a lot of missing data. But
after looking at the missing data based on columns, we won’t need to fix
any of the mssing data since we won’t need any of the missing data
columns. The columns we will need are ‘country’, ‘country_long’,
‘capacity_mw’ and ‘primary_fuel’.
4.2 Data Exploration
Top Country Electricity Generation and Share
Top Electricity Generation
#> country country_long name gppd_idnr capacity_mw latitude
#> 10291 FRA France ARRIGHI WRI1002687 254.00 48.7872
#> 10292 FRA France ASTON WRI1002688 104.00 42.7770
#> 10293 FRA France AVIGNON WRI1002689 126.00 43.9760
#> 10294 FRA France Ablaincourt-Pressoir WRI1024142 14.35 49.8414
#> 10295 FRA France Ablainzevelle WRI1024534 10.00 50.1529
#> 10296 FRA France Achiet-le-Grand WRI1024086 18.00 50.1327
#> longitude primary_fuel other_fuel1 other_fuel2 other_fuel3
#> 10291 2.4033 Oil <NA> <NA> NA
#> 10292 1.6770 Hydro <NA> <NA> NA
#> 10293 4.8170 Hydro <NA> <NA> NA
#> 10294 2.8247 Wind <NA> <NA> NA
#> 10295 2.7410 Wind <NA> <NA> NA
#> 10296 2.7791 Wind <NA> <NA> NA
#> commissioning_year owner source
#> 10291 NA <NA> RTE Transmission Operator
#> 10292 NA <NA> RTE Transmission Operator
#> 10293 NA <NA> RTE Transmission Operator
#> 10294 NA <NA> Open Power System Data
#> 10295 NA <NA> Open Power System Data
#> 10296 NA <NA> Open Power System Data
#> url
#> 10291 http://clients.rte-france.com/lang/an/visiteurs/vie/prod/parc_reference.jsp
#> 10292 http://clients.rte-france.com/lang/an/visiteurs/vie/prod/parc_reference.jsp
#> 10293 http://clients.rte-france.com/lang/an/visiteurs/vie/prod/parc_reference.jsp
#> 10294 http://data.open-power-system-data.org/renewable_power_plants/2016-10-21/
#> 10295 http://data.open-power-system-data.org/renewable_power_plants/2016-10-21/
#> 10296 http://data.open-power-system-data.org/renewable_power_plants/2016-10-21/
#> geolocation_source wepp_id year_of_capacity_data generation_gwh_2013
#> 10291 CARMA 1014623 NA NA
#> 10292 GEODB 1014631 NA NA
#> 10293 GEODB 1013202 NA NA
#> 10294 Open Power System Data <NA> NA NA
#> 10295 Open Power System Data 1086105 NA NA
#> 10296 Open Power System Data <NA> NA NA
#> generation_gwh_2014 generation_gwh_2015 generation_gwh_2016
#> 10291 NA 9.619 6.998
#> 10292 NA NA NA
#> 10293 NA NA NA
#> 10294 NA NA NA
#> 10295 NA NA NA
#> 10296 NA NA NA
#> generation_gwh_2017 generation_gwh_2018 generation_gwh_2019
#> 10291 35.608 NA NA
#> 10292 NA NA NA
#> 10293 NA NA NA
#> 10294 NA NA NA
#> 10295 NA NA NA
#> 10296 NA NA NA
#> generation_data_source estimated_generation_gwh_2013
#> 10291 JRC-PPDB-OPEN NA
#> 10292 <NA> 295.74
#> 10293 <NA> 546.92
#> 10294 <NA> NA
#> 10295 <NA> NA
#> 10296 <NA> NA
#> estimated_generation_gwh_2014 estimated_generation_gwh_2015
#> 10291 NA NA
#> 10292 301.46 352.24
#> 10293 587.61 374.82
#> 10294 NA NA
#> 10295 NA NA
#> 10296 NA NA
#> estimated_generation_gwh_2016 estimated_generation_gwh_2017
#> 10291 NA 271.68
#> 10292 302.29 352.24
#> 10293 379.85 459.52
#> 10294 NA 26.24
#> 10295 NA 18.28
#> 10296 NA 32.91
#> estimated_generation_note_2013 estimated_generation_note_2014
#> 10291 NO-ESTIMATION NO-ESTIMATION
#> 10292 HYDRO-V1 HYDRO-V1
#> 10293 HYDRO-V1 HYDRO-V1
#> 10294 NO-ESTIMATION NO-ESTIMATION
#> 10295 NO-ESTIMATION NO-ESTIMATION
#> 10296 NO-ESTIMATION NO-ESTIMATION
#> estimated_generation_note_2015 estimated_generation_note_2016
#> 10291 NO-ESTIMATION NO-ESTIMATION
#> 10292 HYDRO-V1 HYDRO-V1
#> 10293 HYDRO-V1 HYDRO-V1
#> 10294 NO-ESTIMATION NO-ESTIMATION
#> 10295 NO-ESTIMATION NO-ESTIMATION
#> 10296 NO-ESTIMATION NO-ESTIMATION
#> estimated_generation_note_2017
#> 10291 CAPACITY-FACTOR-V1
#> 10292 HYDRO-V1
#> 10293 HYDRO-V1
#> 10294 CAPACITY-FACTOR-V1
#> 10295 CAPACITY-FACTOR-V1
#> 10296 CAPACITY-FACTOR-V1
#> [1] "FRA" "DEU" "JPN" "RUS" "USA"
5.2.1 Statistical Analysis
#> # A tibble: 5 × 5
#> country_long longitude latitude electricGeneration countryCode
#> <chr> <dbl> <dbl> <dbl> <chr>
#> 1 France 2.05 44.7 51.3 FRA
#> 2 Germany 10.7 50.9 85.6 DEU
#> 3 Japan 137. 35.9 413. JPN
#> 4 Russia 61.4 54.7 419. RUS
#> 5 United States of America -94.1 39.0 123. USA
Here we can see the world map in an interactive plot where we can see
the electricity generation with nuclear energy on the top 5 countries
which produce the most nuclear energy. Here we can see that Japan and
Russia is really similar in electric generation and US in 2nd, France in
3rd, and Germany in 4th.
Top Electricity Share
#> country country_long name gppd_idnr capacity_mw latitude
#> 329 ARM Armenia Armenian-2 WRI1019028 375 40.1805
#> 330 ARM Armenia Hrazadan WRI1019027 1110 40.5640
#> 331 ARM Armenia New Yerevan WRI1019026 271 40.1152
#> 332 ARM Armenia Sevan-Hrazdan Cascade WRI1003805 561 40.5078
#> 333 ARM Armenia Shamb WRI1019030 170 39.4743
#> 334 ARM Armenia Spandaryan WRI1019031 76 39.6494
#> longitude primary_fuel other_fuel1 other_fuel2 other_fuel3
#> 329 44.1498 Nuclear <NA> <NA> NA
#> 330 44.7479 Gas <NA> <NA> NA
#> 331 44.4973 Gas <NA> <NA> NA
#> 332 44.7606 Hydro <NA> <NA> NA
#> 333 46.1306 Hydro <NA> <NA> NA
#> 334 45.8500 Hydro <NA> <NA> NA
#> commissioning_year owner
#> 329 1980 Armenian Nuclear Power Company
#> 330 NA Hrazdan Energy Company
#> 331 2010 Yerevan TPP
#> 332 NA RusHydro
#> 333 1978 Ministry of Energy an Natural Resources
#> 334 1989 Ministry of Energy an Natural Resources
#> source
#> 329 IAEA
#> 330 Armenia Ministry of Energy and Natural Resources
#> 331 Armenia Ministry of Energy and Natural Resources
#> 332 Armenia Ministry of Energy and Natural Resources
#> 333 Armenia Ministry of Energy and Natural Resources
#> 334 Armenia Ministry of Energy and Natural Resources
#> url
#> 329 https://www.iaea.org/PRIS/CountryStatistics/ReactorDetails.aspx?current=2
#> 330 http://www.minenergy.am/en/page/532
#> 331 http://www.minenergy.am/en/page/531
#> 332 http://www.minenergy.am/en/page/534
#> 333 http://www.minenergy.am/en/page/533
#> 334 http://www.minenergy.am/en/page/533
#> geolocation_source wepp_id year_of_capacity_data generation_gwh_2013
#> 329 GEODB 1010334 NA NA
#> 330 GEODB 1010329 NA NA
#> 331 WRI <NA> NA NA
#> 332 GEODB <NA> NA NA
#> 333 GEODB <NA> NA NA
#> 334 GEODB <NA> NA NA
#> generation_gwh_2014 generation_gwh_2015 generation_gwh_2016
#> 329 NA NA NA
#> 330 NA NA NA
#> 331 NA NA NA
#> 332 NA NA NA
#> 333 NA NA NA
#> 334 NA NA NA
#> generation_gwh_2017 generation_gwh_2018 generation_gwh_2019
#> 329 NA NA NA
#> 330 NA NA NA
#> 331 NA NA NA
#> 332 NA NA NA
#> 333 NA NA NA
#> 334 NA NA NA
#> generation_data_source estimated_generation_gwh_2013
#> 329 <NA> NA
#> 330 <NA> NA
#> 331 <NA> NA
#> 332 <NA> 847.52
#> 333 <NA> 254.59
#> 334 <NA> 91.89
#> estimated_generation_gwh_2014 estimated_generation_gwh_2015
#> 329 NA NA
#> 330 NA NA
#> 331 NA NA
#> 332 854.95 838.63
#> 333 248.21 225.18
#> 334 59.65 134.22
#> estimated_generation_gwh_2016 estimated_generation_gwh_2017
#> 329 NA 2411.04
#> 330 NA 6712.82
#> 331 NA 1638.89
#> 332 846.61 853.67
#> 333 234.89 226.04
#> 334 106.80 91.89
#> estimated_generation_note_2013 estimated_generation_note_2014
#> 329 NO-ESTIMATION NO-ESTIMATION
#> 330 NO-ESTIMATION NO-ESTIMATION
#> 331 NO-ESTIMATION NO-ESTIMATION
#> 332 HYDRO-V1 HYDRO-V1
#> 333 HYDRO-V1 HYDRO-V1
#> 334 HYDRO-V1 HYDRO-V1
#> estimated_generation_note_2015 estimated_generation_note_2016
#> 329 NO-ESTIMATION NO-ESTIMATION
#> 330 NO-ESTIMATION NO-ESTIMATION
#> 331 NO-ESTIMATION NO-ESTIMATION
#> 332 HYDRO-V1 HYDRO-V1
#> 333 HYDRO-V1 HYDRO-V1
#> 334 HYDRO-V1 HYDRO-V1
#> estimated_generation_note_2017
#> 329 CAPACITY-FACTOR-V1
#> 330 CAPACITY-FACTOR-V1
#> 331 CAPACITY-FACTOR-V1
#> 332 HYDRO-V1
#> 333 HYDRO-V1
#> 334 HYDRO-V1
5.2.2 Statistical Analysis
#> # A tibble: 5 × 5
#> country_long longitude latitude electricGeneration countryCode
#> <chr> <dbl> <dbl> <dbl> <chr>
#> 1 Armenia 45.1 40.0 409. ARM
#> 2 Bulgaria 25.4 42.7 215. BGR
#> 3 Hungary 19.2 47.3 349. HUN
#> 4 Sweden 16.2 61.7 157. SWE
#> 5 Switzerland 8.28 46.7 78.1 CHE
Here we can see the world map in an interactive plot where we can see
the electricity generation with nuclear energy on the top 5 countries
which share the most nuclear energy. Here we can see that Armenia is
1st, then Hungary, then Bulgaria, then Sweden then Switzerland.
Main Source of Fuel for Top Countries with Most Electricity
Generation
#> # A tibble: 6 × 4
#> country_long primary_fuel count meanPower
#> <chr> <chr> <int> <dbl>
#> 1 France Biomass 148 5.36
#> 2 France Coal 5 715
#> 3 France Gas 9 556.
#> 4 France Geothermal 1 4.5
#> 5 France Hydro 429 45.5
#> 6 France Nuclear 19 3323.
#> [1] 5
Here we can see that from the top 5 countries that used the most
nuclear energy power also has used nuclear energy as their main power
source. Gas and Coal have a similar height in use while other pwer
source are low in use. From this we can conclude that Nuclear energy is
a good use of a power source and being Coal or Gas as an
alternative.
2.3 Data Summary
Nuclear Energy Overview over the Years
#> Rows: 614 Columns: 7
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (2): Month, Nuclear Generating Units, Total Operable Units
#> dbl (5): Year, Nuclear Generating Units, Net Summer Capacity, Nuclear Electr...
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> Year Month Nuclear_Generating_Units,_Total_Operable_Units
#> 1 1973 January Not Available
#> 2 1973 February Not Available
#> 3 1973 March Not Available
#> 4 1973 April Not Available
#> 5 1973 May Not Available
#> 6 1973 June Not Available
#> Nuclear_Generating_Units,_Net_Summer_Capacity
#> 1 14.533
#> 2 14.533
#> 3 15.314
#> 4 15.314
#> 5 16.174
#> 6 18.729
#> Nuclear_Electricity_Net_Generation
#> 1 6246
#> 2 5928
#> 3 6649
#> 4 5876
#> 5 5697
#> 6 6784
#> Nuclear_Share_of_Electricity_Net_Generation
#> 1 3.9
#> 2 4.1
#> 3 4.5
#> 4 4.2
#> 5 3.9
#> 6 4.2
#> Nuclear_Generating_Units,_Capacity_Factor
#> 1 57.8
#> 2 60.7
#> 3 58.4
#> 4 53.4
#> 5 47.3
#> 6 50.3
#> Year Month
#> Min. :1973 Length:614
#> 1st Qu.:1985 Class :character
#> Median :1998 Mode :character
#> Mean :1998
#> 3rd Qu.:2011
#> Max. :2024
#> Nuclear_Generating_Units,_Total_Operable_Units
#> Length:614
#> Class :character
#> Mode :character
#>
#>
#>
#> Nuclear_Generating_Units,_Net_Summer_Capacity
#> Min. : 14.53
#> 1st Qu.: 78.71
#> Median : 98.53
#> Mean : 85.61
#> 3rd Qu.: 99.63
#> Max. :102.21
#> Nuclear_Electricity_Net_Generation Nuclear_Share_of_Electricity_Net_Generation
#> Min. : 5697 Min. : 3.90
#> 1st Qu.:31482 1st Qu.:15.53
#> Median :57362 Median :18.80
#> Mean :49806 Mean :17.22
#> 3rd Qu.:65169 3rd Qu.:20.10
#> Max. :74649 Max. :22.90
#> Nuclear_Generating_Units,_Capacity_Factor
#> Min. : 34.60
#> 1st Qu.: 61.02
#> Median : 79.15
#> Mean : 76.50
#> 3rd Qu.: 91.88
#> Max. :101.60
#> 'data.frame': 614 obs. of 7 variables:
#> $ Year : num 1973 1973 1973 1973 1973 ...
#> $ Month : chr "January" "February" "March" "April" ...
#> $ Nuclear_Generating_Units,_Total_Operable_Units: chr "Not Available" "Not Available" "Not Available" "Not Available" ...
#> $ Nuclear_Generating_Units,_Net_Summer_Capacity : num 14.5 14.5 15.3 15.3 16.2 ...
#> $ Nuclear_Electricity_Net_Generation : num 6246 5928 6649 5876 5697 ...
#> $ Nuclear_Share_of_Electricity_Net_Generation : num 3.9 4.1 4.5 4.2 3.9 4.2 4 4.4 5 4.9 ...
#> $ Nuclear_Generating_Units,_Capacity_Factor : num 57.8 60.7 58.4 53.4 47.3 50.3 50 54.5 56.9 49.8 ...
3.3 Data Preprocessing
Missing Data and Filling
#> [1] 0
#> Year
#> 0
#> Month
#> 0
#> Nuclear_Generating_Units,_Total_Operable_Units
#> 0
#> Nuclear_Generating_Units,_Net_Summer_Capacity
#> 0
#> Nuclear_Electricity_Net_Generation
#> 0
#> Nuclear_Share_of_Electricity_Net_Generation
#> 0
#> Nuclear_Generating_Units,_Capacity_Factor
#> 0
Data Handling
#> Year Month Nuclear_Generating_Units,_Total_Operable_Units
#> 1 2014 January 100
#> 2 2014 February 100
#> 3 2014 March 100
#> 4 2014 April 100
#> 5 2014 May 100
#> 6 2014 June 100
#> Nuclear_Generating_Units,_Net_Summer_Capacity
#> 1 99.182
#> 2 99.182
#> 3 99.182
#> 4 99.182
#> 5 99.182
#> 6 99.182
#> Nuclear_Electricity_Net_Generation
#> 1 73163
#> 2 62639
#> 3 62397
#> 4 56385
#> 5 62947
#> 6 68138
#> Nuclear_Share_of_Electricity_Net_Generation
#> 1 19.4
#> 2 19.3
#> 3 18.8
#> 4 18.9
#> 5 19.4
#> 6 19.0
#> Nuclear_Generating_Units,_Capacity_Factor
#> 1 99.1
#> 2 94.0
#> 3 84.5
#> 4 78.8
#> 5 85.2
#> 6 95.4
4.3 Data Exploration
Nuclear Generating Units
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> 55290 62852 65869 66160 69730 74649
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> 92.00 93.00 98.00 96.52 99.00 100.00
Correlation between Total Electricity Generation and Total
Generating Units
#> [1] 0.2141611
Electicity Generation Over the Years
From the graph above, we can see that the electricity produced by
nuclear generators have an incline from 2014 - 2019 and after that had a
major drop until 2022 and has only went up since 2023. We can assume
that the drop was caused by the pandemic where most workers were asked
to work hom or don’t work. This caused nuclear generators to stop
working or less working. Post COVID gives a good result where more
generators seems to be working again.
Generator Units over the Years
From the Graph shown, we can conclude that the operational nuclear
generators also dropped from 2019 - 2022 since of COVID-19. There seems
to be an incline in operational nuclear generators post COVID
(2023-2024) where people can work more.
5.3 Statistical Analysis
T-Test to find out if Electricity Drop is caused by COVID
#>
#> Welch Two Sample t-test
#>
#> data: pre_covid$meanGeneration and post_covid$meanGeneration
#> t = 3.3727, df = 5.1815, p-value = 0.01877
#> alternative hypothesis: true difference in means is not equal to 0
#> 95 percent confidence interval:
#> 407.6291 2909.4265
#> sample estimates:
#> mean of x mean of y
#> 66965.03 65306.50
Based on the statistical analysis, there is evidence to suggest that
there is a difference in power generation between the pre-COVID and
post-COVID periods. The p-value (0.01877) indicates statistical
significance, and the confidence interval does not include 0. Post-COVID
generation appears to be lower than pre-COVID generation.
Correlation between Average Units and Average Power Generation over
the Years
#> [1] 0.7437131
1 = Strong Positive Correlation 0 = No Positive Correlation -1 =
Strong Negative Correlation
According to the correlation calculation above we can conclude that
number of operational units has a strong positive correlation with the
average power electricity generation.
Discussion
Based on our analysis we can see that Nuclear Energy has been used by
most countries especially the top 5 countries on our analysis. We now
know that the trend of the use of Nuclear Energy has been used most of
the time before the pandemic, has dropped drastically during it and is
trying to rise up again post pandemic. We also have additional info
based on other source of fuel being gas and hydro as an alternative
energy source if nuclear energy isn’t working out. Coal and Oil are high
up based on our findings but it isn’t a good choice since those fuel
source are limited. We should also increase our other fuel sources such
as wind and solar fuel as they aren’t limited fuel energy source.
Conclusion
After this whole Analysis, we can conclude that Nuclear Energy is a
good power source to use and is a good long term power source to use for
the future. There seems to be an incline in Nuclear power use and more
countries are using more as a source of power. This analysis can be
researched further in the case of in the coming future or maybe in more
specific areas around the world or maybe added more analysis surrounding
nuclear energy.
References
Data Set Link: link